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Wireless Sensors and wireless sensor networks have been used broadly in academic communities. That is owing to increasingly development of small scale equipment in engineering that prepares enormous applications. Numerous researches have been done in order to using of these sensors as well as establishing them as a network and large variety of solutions have been suggested. One heuristic method to modeling wireless sensor networks is distributed adaptive modeling. Processing is done in fully distributed manner at this way. An adaptive network contains a number of nodes those are capable to learn and adapt. Every node exchanges its data with neighbor nodes so as to the network could finally solve an estimation or interference problem. In this paper, at first, the position of distributed adaptive processing will be explained, then we review some proposed strategies for adaptive modeling and after that simulation results will be compared.